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Multi-cohort forest management in northern hardwood stands may well be the best way to successfully regenerate tree species of intermediate shade tolerance, such as yellow birch (Betula alleghaniensis Britt.). The creation of large enough gaps in the canopy favors increased light availability within the opening, while soil scarification provides suitable germination seedbeds. Evidence of these methods’ success nonetheless remains mostly the purview of experimental studies rather than operational tests. In Quebec, Canada, the multi-cohort methods promoted include group selection cutting and patch cutting. The present study tested their implementation at an operational scale and over a large territory in both hardwood-dominated and mixedwood stands. We assessed their efficacy in promoting natural regeneration of commercial hardwood trees, notably yellow birch and sugar maple (Acer saccharum Marsh.). We conducted regeneration surveys at 2, 5, 10, and 15 years after harvest. Overall, group selection and patch cuttings were successful in regenerating the target species. Yellow birch, for instance, showed a mean stocking around 60% and a mean sapling density around 3400 stems ha−1 after 15 years. We compared several variables for measuring regeneration in early years, and found that the relative abundance, the stocking based on one stem per sampling unit, and the mean maximum height were good predictors of the relative presence of yellow birch and sugar maple in 15-year-old canopy openings. Using smaller sampling units (6.25 m2 rather than 25 m2) and waiting until year 5 may be more useful for making such predictions. In addition, there was an important turnover in vertical dominance in these openings. Non-commercial woody competitors were frequently dominant in early years but were often replaced by commercial hardwoods, notably yellow birch. We propose certain thresholds for assessing the success of post-harvest regeneration and for evaluating the need for a cleaning treatment.
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Individual tree recruitment is an important element needed to understand stand dynamics, as it influences both stand composition and productivity. Forest growth simulators usually include recruitment models. The quality of recruitment predictions can have long-term impacts on estimations of forest growth, ecosystem health and the commercial utility of managed forests. The main objective of this study was to develop a recruitment model for commercial-size trees (i.e., trees with a diameter at breast height > 9 cm) of 10 species groups using different dendrometric and environmental variables. The resulting model will be included in a growth simulator used to support forest management planning. We hypothesized that accounting for sapling density as a covariate would improve the recruitment model's predictive performance. Using empirical data from periodically measured permanent sample plots (1982–2019) located throughout the managed mixed hardwood forests of Quebec, we constructed models with and without sapling-related covariates and compared them on the basis of cross-validation model performance statistics. Our results show that including sapling density significantly improved model performance. From this, we conclude that adding sapling density as a covariate can significantly improve a recruitment model's predictive power for eastern mixed hardwood forests.